Identifying and quantifying sources of temporal and spatial uncertainty in assessing salmonid responses to watershed‐scale restoration. (8th March 2022) - Rogers, Mark; Selker, John; Peterson, James; Arismendi, Ivan
Abstract: Despite significant investments in watershed‐scale restoration projects, evaluation of their impacts on salmonids is often limited by inadequate experimental design. This project aimed to strengthen study designs by identifying and quantifying sources of temporal and spatial uncertainty while assessing population‐level salmonid responses in Before‐After‐Control‐Impact (BACI) restoration experiments. To evaluate sources of temporal uncertainty, meta‐analysis of 32 annual BACI experiments from the Pacific Northwest, USA was conducted. Experimental error was determined to be a function of the total temporal variation of both restoration and control salmonid population metrics and the degree of covariation, or synchrony, between these metrics ( r 2 = 1). However, synchrony was both weak ( ρ ¯ = 0.18) and unrelated to experimental error ( r = 0.01) while temporal variability was found to account for 91% of this error. Because synchrony did not reduce experimental error, we conclude that BACI designs will not normally exhibit greater power over uncontrolled Before‐After (BA) designs. To evaluate spatial uncertainty, hierarchical BACI designs were simulated. It was found that spatial variability of hypothetical steelhead ( Oncorhynchus mykiss ) growth values within watersheds can cause mis‐estimation of the restoration effect and reduce power. While hierarchical BACI designs can examine both reach and watershed‐scale restoration effects simultaneously, due to probable mis‐estimation of the restoration effect size, these scales should be examined separately. Paired‐reach designs such as Extensive Post‐Treatment (EPT) provide powerful replicated local‐scale restoration experiments, which can build understanding of restoration‐ecological mechanisms. Knowledge gained from reach‐scale experiments should then be implemented on watershed‐scales and monitored within a non‐hierarchical framework.